Char-
Year: 2019
Type: conference-paper
Abstract: We explore how well a sequence labeling approach, namely, recurrent neural network, is suited for the task of resource-poor and POS tagging free word stress detection in the Russian, Ukranian, Belarusian languages. We present new datasets, annotated with the word stress, for the three languages and compare several RNN models trained on three languages and explore possible applications of the transfer learning for the task. We show that it is possible to train a model in a cross-lingual setting and that using additional languages improves the quality of the results.
DOI: 10.18653/v1/w19-1404
Authors: Ekaterina Chernyak, Maria Ponomareva, Kirill Milintsevich
Institution: University of Tartu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W3088846751